This paper evaluates the performance of Wi-Fi networks for interactive Virtual Reality (VR) streaming with adaptive bitrate control. It focuses on the interaction between VR traffic characteristics and Wi-Fi link-layer mechanisms, studying how this relationship impacts key performance indicators such as throughput, latency, and user scalability. We begin by outlining the architecture, operation, traffic patterns, and performance demands of cloud/edge split-rendering VR systems. Then, using simulations, we investigate both single-user scenarios—examining the effects of modulation and coding schemes (MCSs) and user-to-access point (AP) distance on bitrate sustainability and latency—and multi-user scenarios, assessing how many concurrent VR users a single AP can support. Results show that the use of adaptive bitrate (ABR) streaming, as exemplified by our NeSt-VR algorithm, significantly outperforms constant bitrate (CBR) approaches, enhancing user capacity and resilience to changing channel propagation conditions. To validate the simulation findings, we conduct an experimental evaluation using Rooms, an open-source eXtended Reality (XR) content creation platform. The experimental results closely match the simulations, reinforcing the conclusion that adaptive bitrate control substantially improves Wi-Fi’s ability to support reliable, multiuser interactive VR streaming.

Large-scale virtual reality (VR) enables novel art forms in large physical environments. A key technical solution in such cases is to split the rendering process between a client and a streamer. In this article, we focused on the peculiarities of VR split rendering and particularly on the performance of Wi-Fi. First, we calculated the network delay budget and then conducted a set of experiments to evaluate the single-user and multi-user performance of VR split rendering systems over Wi-Fi in terms of latency. Our findings were summarized as recommendations on: i) the frame rate, ii) the encoding bitrate, iii) the signal strength, iv) the channel bandwidth, and v) the multiple access techniques. In particular, our multi-user tests highlighted cases where using the highest settings or latest features of Wi-Fi can compromise performance. Finally, we applied our recommendations to a large-scale multi-user case study that took place physically in the multi-purpose hall of our university campus and virtually in the Turret Singers environment of SteamVR Home. This article serves as a reference to the critical aspects of VR split rendering systems over Wi-Fi.

Interactive Virtual Reality (VR) streaming over Wi-Fi networks encounters significant challenges due to bandwidth fluctuations caused by channel contention and user mobility. Adaptive BitRate (ABR) algorithms dynamically adjust video encoding bitrate based on the available network capacity, aiming to maximize image quality while mitigating congestion and preserving the user's Quality of Experience (QoE). In this paper, we experiment with ABR algorithms for VR streaming using Air Light VR (ALVR), an open-source VR streaming solution. We extend ALVR with a comprehensive set of metrics that provide a robust characterization of the network state, enabling more informed bitrate adjustments. To demonstrate the utility of these performance indicators, we develop and test the Network-aware Step-wise ABR algorithm for VR streaming (NeSt-VR). Results validate the accuracy of the implemented network performance metrics and demonstrate NeSt-VR's adaptation capabilities.

Virtual Reality (VR) streaming enables end-users to seamlessly immerse themselves in interactive virtual environments using even low-end devices. However, the quality of the VR experience heavily relies on Wireless Fidelity (Wi-Fi) performance, since it serves as the last hop in the network chain. Our study delves into the intricate interplay between Wi-Fi and VR traffic, drawing upon empirical data and leveraging a Wi-Fi simulator. In this work, we further evaluate Wi-Fi’s suitability for VR streaming in terms of the Quality of Service (QoS) it provides. In particular, we employ Unity Render Streaming to remotely stream real-time VR gaming content over Wi-Fi 6 using Web Real-Time Communication (WebRTC), considering a server physically located at the network’s edge, near the end user. Our findings demonstrate the system’s sustained network performance, showcasing minimal round-trip time (RTT) and jitter at 60 and 90 frames per second (fps). In addition, we uncover the characteristics and patterns of the generated traffic streams, unveiling a distinctive video transmission approach inherent to WebRTC-based services: the systematic packetization of video frames (VFs) and their transmission in discrete batches at regular intervals, regardless of the targeted frame rate. This interval-based transmission strategy maintains consistent video packet delays across video frame rates but leads to increased Wi-Fi airtime consumption. Our results demonstrate that shortening the interval between batches is advantageous, as it enhances Wi-Fi efficiency and reduces delays in delivering complete frames.